Geo Joy
Senior ML Specialist at F-Secure Corporation
Bengaluru, Karnataka, India
Summary
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Senior🎓
Top SchoolGeo Joy is a Senior ML Specialist and pragmatic cyber architect with 11 years of hands-on experience building startups-grade products across web, mobile, cloud, blockchain, trading platforms and security-focused AI. Now leading the AI team in F-Secure’s Scam Unit, he designs on-device ML that must outthink adaptive, highly personal scams rather than rely on brittle rule sets. A self-taught builder who moved from freelance web work to co-founding and architecting multiple companies, he blends deep practical engineering with threat-minded design—security has always been his lens. He mentors teams, ships resilient cloud architectures at scale, and translates complex AI/security topics for practitioners and curious audiences through his Breach Guru channel. Notably, his background includes exposing real-world security gaps and a career pattern of learning by breaking and fixing systems, which informs his adversarial-first approach to product design.
11 years of coding experience
13 years of employment as a software developer
Christ SchoolMaster of Business Administration - MBA (online), Information Technology, Master of Business Administration - MBA (online), Information Technology at Amity University OnlineBachelor of Engineering (B.E.), Electronics and Communications Engineering, Bachelor of Engineering (B.E.), Electronics and Communications Engineering at Visvesvaraya Technological UniversityP.U.C., P.C.M.E., P.U.C., P.C.M.E. at Christ University, Bangalore
English, Malayalam, Hindi, Tamil, Norwegian
Github Skills (73)
time-series-forecasting10
pyaudio9
api9
exchange9
trading9
gevent9
deep-learning9
cryptocurrency9
long-polling9
ethereum9
bitcoin9
crypto8
python-socket8
cryptocurrencies8
python8
Programming languages (8)
Github contributions (5)
Geo-Joy/geo-joy-blog
Jan 2018 - Apr 2021
my personal blog hosted on github
Contributions:45 pushes, 1 branch in 3 years 3 months
hostedjekyllmy-personal-blog
Geo-Joy/Deep-Learning-for-Time-Series-Forecasting
Sep 2018 - Jan 2019
This repository is designed to teach you, step-by-step, how to develop deep learning methods for time series forecasting with concrete and executable examples in Python.
Contributions:18 commits, 14 pushes, 1 branch in 3 months
deep-learningpythontime-series-forecastingdeep-learning-time-seriestime-series-prediction
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